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亚马逊地区的新冠疫情动态:政府否认主义的历史及第三波疫情风险

Dynamics of COVID-19 in Amazonia: A history of government denialism and the risk of a third wave.

作者信息

Ferrante Lucas, Duczmal Luiz Henrique, Capanema Eduardo, Steinmetz Wilhelm Alexander Cardoso, Almeida Alexandre Celestino Leite, Leão Jeremias, Vassão Ruth Camargo, Fearnside Philip Martin, Tupinambás Unaí

机构信息

Instituto Nacional de Pesquisas da Amazônia (INPA), Programa de Pós-Graduação em Biologia (Ecologia), Manaus, Amazonas, Brazil.

Universidade Federal de Minas Gerais (UFMG), Department of Statistics, Belo Horizonte, Minas Gerais, Brazil.

出版信息

Prev Med Rep. 2022 Feb 28;26:101752. doi: 10.1016/j.pmedr.2022.101752. eCollection 2022 Apr.

Abstract

The city of Manaus (the capital of Brazil's state of Amazonas) has become a key location for understanding the dynamics of the global pandemic of COVID-19. Different groups of scientists have foreseen different scenarios, such as the second wave or that Manaus could escape such a wave by having reached herd immunity. Here we test five hypotheses that explain the second wave of COVID-19 in Manaus: 1) The greater transmissibility of the Amazonian (gamma or P.1) variant is responsible for the second wave; 2) SARS-CoV-2 infection levels during the first wave were overestimated by those foreseeing herd immunity, and the population remained below this threshold when the second wave began at the beginning of December 2020; 3) Antibodies acquired from infection by one lineage do not confer immunity against other lineages; 4) Loss of immunity has generated a feedback phenomenon among infected people, which could generate future waves, and 5) A combination of the foregoing hypotheses. We also evaluated the possibility of a third wave in Manaus despite advances in vaccination, the new wave being due to the introduction of the delta variant in the region and the loss of immunity from natural contact with the virus. We developed a multi-strain SEIRS (Susceptible-Exposed-Infected-Removed-Susceptible) model and fed it with data for Manaus on mobility, COVID-19 hospitalizations, numbers of cases and deaths. Our model contemplated the current vaccination rates for all vaccines applied in Manaus and the individual protection rates already known for each vaccine. Our results indicate that the SARS-CoV-2 gamma (P.1) strain that originated in the Amazon region is not the cause of the second wave of COVID-19 in Manaus, but rather this strain originated during the second wave and became predominant in January 2021. Our multi-strain SEIRS model indicates that neither the doubled transmission rate of the gamma variant nor the loss of immunity alone is sufficient to explain the sudden rise of hospitalizations in late December 2020. Our results also indicate that the most plausible explanation for the current second wave is a SARS-CoV-2 infection level at around 50% of the population in early December 2020, together with loss of population immunity and early relaxation of restrictive measures. The most-plausible model indicates that contact with one strain does not provide protection against other strains and that the gamma variant has a transmissibility rate twice that of the original SARS-CoV-2 strain. Our model also shows that, despite the advance of vaccination, and even if future vaccination advances at a steady pace, the introduction of the delta variant or other new variants could cause a new wave of COVID-19.

摘要

马瑙斯市(巴西亚马逊州首府)已成为了解新冠病毒全球大流行动态的关键地点。不同的科学家群体预测了不同的情况,比如第二波疫情,或者马瑙斯可能通过实现群体免疫而避免出现这样一波疫情。在此,我们检验了五个解释马瑙斯第二波新冠疫情的假设:1)亚马逊(伽马或P.1)变体更强的传播性导致了第二波疫情;2)预测群体免疫的人高估了第一波疫情期间的新冠病毒感染水平,在2020年12月初第二波疫情开始时,该地区人口仍低于这一阈值;3)感染一个谱系所获得的抗体不能提供针对其他谱系的免疫力;4)免疫力丧失在感染者中产生了一种反馈现象,这可能引发未来的疫情波,以及5)上述假设的综合。我们还评估了尽管有疫苗接种进展,马瑙斯仍出现第三波疫情的可能性,这一新波疫情是由于该地区引入了德尔塔变体以及与病毒自然接触所产生的免疫力丧失。我们开发了一个多毒株SEIRS(易感-暴露-感染-康复-易感)模型,并输入了马瑙斯关于流动性、新冠住院情况、病例数和死亡数的数据。我们的模型考虑了马瑙斯所接种的所有疫苗的当前接种率以及每种疫苗已知的个体保护率。我们的结果表明,源自亚马逊地区的新冠病毒伽马(P.1)毒株不是马瑙斯第二波新冠疫情的原因,而是该毒株在第二波疫情期间出现,并于2021年1月成为优势毒株。我们的多毒株SEIRS模型表明,伽马变体两倍的传播率或单独的免疫力丧失都不足以解释2020年12月底住院人数的突然增加。我们的结果还表明,对当前第二波疫情最合理的解释是,2020年12月初约50%的人口感染了新冠病毒,同时群体免疫力丧失以及限制措施过早放松。最合理的模型表明,接触一种毒株不能提供针对其他毒株的保护,并且伽马变体的传播率是原始新冠病毒毒株的两倍。我们的模型还表明,尽管有疫苗接种进展,而且即使未来疫苗接种稳步推进,引入德尔塔变体或其他新变体仍可能引发新一轮新冠疫情。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e03d/8891711/ad506d43190f/gr1.jpg

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